Computer Science

Data Pipelines with TensorFlow Data Services

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Coursera With GroupifyAI

This AI course instructs students on the optimization of input pipelines, dataset segmentation, data preparation for training pipelines, and efficient ETL tasks using TensorFlow Data Services APIs.

Key AI Functions:Tensorflow, Extraction, Transformation And Loading (ETL), Artificial Neural Network, TensorFlow Datasets, Data Pipelines

Description for Data Pipelines with TensorFlow Data Services

  • Utilize the Tensorflow Data Services APIs to execute ETL duties in an efficient manner.
  • Create train/validation/test divisions for any dataset, whether it is custom or available in the TensorFlow Hub Dataset library, by utilizing the divisions API.
  • Utilize a variety of modules and functions within the TFDS API to prepare your data for training pipelines.
  • Increase the efficacy of your workflow by identifying bottlenecks in your input pipelines and implementing input parallelization.
  • Level: Intermediate

    Certification Degree: Yes

    Languages the Course is Available: 21

    Offered by: On Coursera provided by DeepLearning.AI

    Duration: 11 hours (approximately)

    Schedule: Flexible

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